Multimodal diffusion for joint design of protein sequence and structure.

ABSTRACT: Computational design of functional proteins is of both fundamental and applied interest. This study introduces a generative framework for co-designing protein sequence and structure in a unified process by modeling their joint distribution, with the goal of enabling cross-modality interactions toward coherent and functional designs. Each residue is represented by three distinct modalities (type, position, and orientation) and modeled using dedicated diffusion processes: multinomial for types, Cartesian for positions, and special orthogonal group SO(3) for orientations. To couple these modalities, we propose a unified architecture, ReverseNet, which employs a shared graph attention encoder to integrate multimodal information and separate projectors to predict each modality. We benchmark our

SUBMITTER: Zhu S 

PROVIDER: S-EPMC12617271 | biostudies-literature | 2025 Dec

REPOSITORIES: biostudies-literature